awslabs.bedrock-kb-retrieval-mcp-server

v1.0.22 safe
4.0
Medium Risk

An AWS Labs Model Context Protocol (MCP) server for Bedrock Knowledge Base Retrieval

🤖 AI Analysis

Final verdict: SAFE

The package appears safe with low risks across most categories. The credential handling could be improved to prevent accidental exposure, but no signs of malicious activity or supply-chain attack are evident.

  • Low network and shell execution risks
  • Moderate credential risk due to potential exposure
  • No suspicious metadata or obfuscation practices
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require internet access or external API interactions.
  • Shell: No shell execution patterns detected, indicating the package does not execute system commands which reduces risk of unauthorized operations.
  • Obfuscation: The obfuscation pattern detected is a common method to extend the package search path and does not indicate malicious intent.
  • Credentials: The credential harvesting patterns detected are likely for legitimate AWS service interaction using environment variables, but there is a moderate risk if these credentials are exposed accidentally.
  • Metadata: The author has only one package, which might indicate a new or less active account, but no other suspicious activities are flagged.

📦 Package Quality Overall: Medium (5.8/10)

✦ High Test Suite 9.0

Test suite present — 8 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 8 test file(s) detected (e.g. __init__.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://awslabs.github.io/mcp/servers/bedrock-kb-retrieval-m
  • Detailed PyPI description (7644 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 42 unique contributor(s) across 100 commits in awslabs/mcp
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • amespace packages. __path__ = __import__('pkgutil').extend_path(__path__, __name__) # Copyright Amazon.com, In
✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 10.0

Found 4 credential access pattern(s)

  • e_client( region_name=os.getenv('AWS_REGION'), profile_name=os.getenv('AWS_PROFILE'),
  • EGION'), profile_name=os.getenv('AWS_PROFILE'), ) kb_agent_mgmt_client = get_bedrock_agen
  • t_client( region_name=os.getenv('AWS_REGION'), profile_name=os.getenv('AWS_PROFILE'),
  • EGION'), profile_name=os.getenv('AWS_PROFILE'), ) except Exception as e: logger.error(f'E
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: users.noreply.github.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository awslabs/mcp appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Amazon Web Services" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with awslabs.bedrock-kb-retrieval-mcp-server 
Create a knowledge base retrieval mini-application using the 'awslabs.bedrock-kb-retrieval-mcp-server' package. This application will serve as a user-friendly interface for querying a knowledge base hosted on AWS Bedrock. The app should allow users to input queries and receive relevant information from the knowledge base in a structured format. Here are the steps and features you need to implement:

1. **Setup**: Begin by installing the necessary packages, including 'awslabs.bedrock-kb-retrieval-mcp-server'. Ensure you have access to an AWS Bedrock environment where your knowledge base is stored.
2. **Configuration**: Configure the MCP server to connect to your specific AWS Bedrock knowledge base. This involves setting up the server to understand the context and structure of the data in your knowledge base.
3. **User Interface**: Develop a simple yet effective user interface where users can type their queries. The UI should be intuitive and easy to navigate.
4. **Query Processing**: Implement functionality within the application to process user queries through the MCP server. This includes sending queries to the server and receiving responses.
5. **Result Display**: Design a feature to display results from the knowledge base in a clear and organized manner. Results could be shown in bullet points, tables, or any other format that enhances readability.
6. **Error Handling**: Include robust error handling mechanisms to manage situations where queries cannot be processed or when there are issues connecting to the knowledge base.
7. **Additional Features**: Consider adding extra functionalities such as query history, the ability to save favorite queries, or even integrating a chatbot interface for more interactive query sessions.

By following these steps and incorporating these features, your application will not only utilize the core capabilities of the 'awslabs.bedrock-kb-retrieval-mcp-server' package but also provide a valuable tool for accessing and utilizing information from your AWS Bedrock knowledge base.

💬 Discussion Feed

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